Can a machine help you invest in shampoo? Coffee? Another consumer product?

Last week, the USV portfolio company CircleUp announced the closing and launch of CircleUp Growth Partners - a $125 million fund that will use a quantitative machine learning approach to invest in early-stage consumer and retail brands.

We believe this is an important evolution towards using data technology to make investment decisions - a theme we at USV have invested in many times ranging from Lending Club to Funding Circle to Numerai. CircleUp Growth Partners is slightly different. The Fund’s thesis is that one can use machine learning to determine early-stage equity decisions in consumer companies. This machine learning platform, Helio, identifies and evaluates companies across billions of data points. The Fund is live right now - Helio recently analyzed 3,400 vitamin and supplement companies and flagged HUM Nutrition as being in the top 3% for brand score. This ultimately led the Fund to make one of its first investments in that company.

The provocative proposition is that a system like this can run these types of analyses at scale and pinpoint brands earlier and with more efficiency than traditional investors. Consumer investors historically have had to spend around 75% of their time sourcing deals manually. Helio is able to automate this entire sourcing process and provide data-driven insights to help companies grow.

Helio has also been applied to two other business lines - credit and marketplace. CircleUp originally operated solely on a marketplace model but has recently launched a credit arm that provides working capital to consumer companies. These three business units all provide data back to the model, which in turn makes each better in its own domain. This is a data network effect - Helio is continually improving.

The focused industry of consumer goods should lend itself well to this approach; consumer packaged goods all share the same business model, and data proliferates across the industry.

Could data-driven investment models like that of Circle Up be extensible to sectors beyond consumer goods? It will be interesting to see how these approaches might affect capital formation more broadly, as data applications move to designing new financial products and services we have not yet even considered.

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